• Skip to primary navigation
  • Skip to main content
  • Skip to footer

Center for Artificial Intelligence and Cybersecurity – AIRI

  • Home
  • About Us
    • Center Activities
    • Vision, Mission and Goals
    • Center Faculty
    • Steering Committee
    • Press
  • Research
    • Scientific Projects
    • Research Papers
  • Laboratories
    • Machine Learning
    • Natural Speech & Language Processing
    • Blockchain Technology
    • Information Processing & Pattern Recognition
    • AI in Medicine
    • Data Mining
    • Computer Vision
    • Complex Networks
    • Human-Computer Interaction
    • Maritime Cybersecurity
    • Autonomous Navigation
    • AI in Mechatronics
    • AI in Education
    • Hybrid Computational Methods
    • Drug Design
    • Legal Aspects of AI
    • Ethically Aligned AI
    • Cultural Complexity
    • Trustworthy and Explainable AI
  • Collaboration
    • Industry Collaboration
    • Industry Projects
    • International Collaboration
  • News
  • Contact
  • Login

Laboratory for Drug Design

The laboratory for Drug Design is focused on peptides, peptide assemblies and their potential new functions. In our interdisciplinary approach we want to combine machine learning and genetic algorithms with experimental validation to develop a more efficient and economical approach compared to the unguided experimental evaluation. We aim to discover patterns in existing data and accelerate the discovery of new catalytic peptides within a relatively small number of experiments.

Head of Laboratory

Daniela Kalafatović, PhD (RITEH)

Laboratory Projects

Design of short catalytic peptides and peptide assemblies (DeShPet)

Applying Machine Learning for the Discovery of Peptides with Catalytic Activity

Laboratory Research Papers

Coupled encoding methods for antimicrobial peptide prediction: How sensitive is a highly accurate model?

Discovery of phosphotyrosine-binding oligopeptides with supramolecular target selectivity

Exploiting Peptide Self-Assembly for the Development of Minimalistic Viral Mimetics

Bottom-Up Design Approach for OBOC Peptide Libraries

Algorithm-supported, mass and sequence diversity-oriented random peptide library design

Customizing morphology, size, and response kinetics of matrix metalloproteinase-responsive nanostructures by systematic peptide design

MSK1 regulates luminal cell differentiation and metastatic dormancy in ER+ breast cancer

Cell-penetrating peptides: Design strategies beyond primary structure and amphipathicity

MMP-9 triggered self-assembly of doxorubicin nanofiber depots halts tumor growth

Alignment of nanostructured tripeptide gels by directional ultrasonication

Exploring the sequence space for (tri-)peptide self-assembly to design and discover new hydrogels

MMP-9 triggered micelle-to-fibre transitions for slow release of doxorubicin

Affiliated Researchers

  • Darijan Jelušić, uni. mag. comp. (RITEH)
  • Daniela Kalafatović, PhD (RITEH)
  • Ena Dražić, mag. med. chem.
  • Goran Mauša, Assist. Prof., PhD (RITEH)
  • Jurica Novak, Assist. Prof., PhD
  • Marko Babić, mag. pharm. inv.
  • Patrizia Janković, PhD
  • Toni Todorovski, Assit. Prof., PhD

Footer

Center for Artificial Intelligence and Cybersecurity
  • jlerga@airi.uniri.hr
  • +385 51 406 500

University of Rijeka

University of Rijeka

About the Center

  • About Us
  • News
  • Privacy Policy
  • Contact

Center Activities

  • Laboratories
  • Scientific Projects
  • Industry Projects
  • Research Papers
  • Industry Collaboration
  • International Collaboration

Footer bottom left

© 2020 Center for Artificial Intelligence and Cybersecurity, all rights reserved.

Designed & developed by Nela Dunato Art & Design